Published on *OpenMx* (http://openmx.psyc.virginia.edu)

By *jlisic*

Created *04/13/2011 - 11:37*

Wed, 04/13/2011 - 11:37 — jlisic [1]

Hi, I've been playing a bit around with SEM models and open-mx and I am having some trouble with derivation of the 'saturated -2 log likelihood' output provided by the summary screen.

Shouldn't the Saturated model be zero always except for some machine error? Instead it tends to be fairly close to a model with 1 degree of freedom.

I might be misunderstanding something but for the saturated model where the Implied model under this condition is equal to the Sample covariance matrix which should yield a discrepancy function of zero.

So, in slightly more explicit terms is this output actually related to the derivation of the -2 * log(Likelihood Ratio) for H_0: Sigma is equal to the Saturated model, where Sigma is the covariance of a multi-variate normal distribution, or is it something else?

Thanks,

Jonathan

**Links:**

[1] http://openmx.psyc.virginia.edu/users/jlisic

[2] http://openmx.psyc.virginia.edu/thread/891

[3] http://openmx.psyc.virginia.edu/thread/873

[4] http://openmx.psyc.virginia.edu/forums/openmx-help/openmx-general-help